{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在Capital Bikeshare （美国 Washington, D.C.的一个共享单车公司）提供的自行车数据上进行回归分析。训练数据为 2011 年的数据，要求预测 2012 年每天的单车共享数量。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.导入必要的工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np  # 矩阵操作\n",
    "import pandas as pd # SQL数据处理\n",
    "\n",
    "from sklearn.metrics import r2_score  #评价回归预测模型的性能\n",
    "\n",
    "import matplotlib.pyplot as plt   #画图\n",
    "import seaborn as sns\n",
    "\n",
    "# 图形出现在Notebook里而不是新窗口\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.数据探索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.1读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# path to where the data lies\n",
    "dpath = '~/Desktop/Bike-Sharing-Dataset/'\n",
    "data = pd.read_csv(dpath + \"day.csv\")\n",
    "\n",
    "#通过观察前5行，了解数据每列（特征）的概况\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.2 数据基本信息"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "样本数目、特征维数 每个特征的类型、空值样本的数目、数据类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(731, 16)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.3 数据探索\n",
    "\n",
    "对数据的探索有助于我们在第三步中根据数据的特点选择合适的模型类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.3.1数据基本信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "instant       0\n",
       "dteday        0\n",
       "season        0\n",
       "yr            0\n",
       "mnth          0\n",
       "holiday       0\n",
       "weekday       0\n",
       "workingday    0\n",
       "weathersit    0\n",
       "temp          0\n",
       "atemp         0\n",
       "hum           0\n",
       "windspeed     0\n",
       "casual        0\n",
       "registered    0\n",
       "cnt           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 查看是否有空值\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.3.2  探索数据\n",
    "查看数据各特征的分布，以及特征之间是否存在相关关系等冗余。\n",
    "\n",
    "我们可以借用可视化工具来直观感觉数据的分布。\n",
    "\n",
    "在Python中，有很多数据可视化途径。 Matplotlib非常强大，也很复杂，不易于学习。 Seaborn是在matplotlib的基础上进行了更高级的API封装，从而使得作图更加容易，在大多数情况下使用seaborn就能做出很具有吸引力的图，而使用matplotlib就能制作具有更多特色的图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此处得到各属性的样本数目、均值、标准差、最小值、1/4分位数（25%）、中位数（50%）、3/4分位数（75%）、最大值 可初步了解各特征的分布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.3.3单变量分布分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 目标y（一天的总租车人数）的直方图／分布\n",
    "fig = plt.figure()\n",
    "sns.distplot(data.cnt.values, bins=30, kde=True)\n",
    "plt.xlabel('Fig 1', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 单个特征散点图\n",
    "plt.scatter(range(data.shape[0]), data[\"cnt\"].values,color='purple')\n",
    "plt.title(\"Fig 2\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.season.values, bins=30, kde=False)\n",
    "plt.xlabel('season', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.yr.values, bins=30, kde=False)\n",
    "plt.xlabel('year', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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6GYOuFvwGvUvFnwe8il6A3wGcTu97/E1JngfcBLwZmKD35uafTHLSrK/zGnpvTHAO8ELgd6rqUeBlwIGqOqX7OPpa5FfSe6GzVfReh+SDI91LqQ+DrhZ8oKoOda8b/i/Arqq6s6p+DNxK73XtfxP4x6ra0b1i4buBp/L4Vy3866o6UFXfBT5J7/VgnsgXq+rTVfUT4O/pvUuSNDYGXS04NOv+/86xfAq91xH/5tGVVfVT4CEe/45U3551/0fd457Isduf3L2jkDQWBl1PFgeA5xxd6F6G9izgWwM81lew07Jg0PVkcQvwiiQbujcxeQvwY+BfB3jsIeBZSX5xlANKS+U/D/WkUFXf6N627QP0TrPcBbyqqh4b4LH3dq9xfX+SFcD5o51WWhxfD12SGuEpF0lqhEGXpEYYdElqhEGXpEYYdElqhEGXpEYYdElqhEGXpEYYdElqxP8D0FnL6Dtu4/oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.mnth.values, bins=30, kde=False)\n",
    "plt.xlabel('month', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.holiday.values, bins=30, kde=False)\n",
    "plt.xlabel('holiday', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.weekday.values, bins=30, kde=False)\n",
    "plt.xlabel('weekday', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.workingday.values, bins=30, kde=False)\n",
    "plt.xlabel('workingday', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.weathersit.values, bins=30, kde=False)\n",
    "plt.xlabel('weather', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.temp.values, bins=30, kde=False)\n",
    "plt.xlabel('temperature', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.atemp.values, bins=30, kde=False)\n",
    "plt.xlabel('atemperature', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.hum.values, bins=30, kde=False)\n",
    "plt.xlabel('humidity', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAENCAYAAAAfTp5aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAEaRJREFUeJzt3XusZWV9xvHvIxcveAM5UATG8TIVtVG0R9DQahUxVi1QBaNYMyrt9KbSaKqoTVNrbaEmVVJp7FTUaQICRQ0jWhUR8JI6OFxEYKggRZhymZGLgMbL6K9/7DV4Opxxr3Nm733mvOf7SU72uu/fy548+2Xttd6VqkKStPg9aKELkCSNhoEuSY0w0CWpEQa6JDXCQJekRhjoktQIA12SGmGgS1IjDHRJasSuk3yzvffeu5YvXz7Jt5SkRe/SSy/9flVNDdtuooG+fPly1q9fP8m3lKRFL8n3+mznKRdJaoSBLkmNMNAlqREGuiQ1wkCXpEYY6JLUCANdkhphoEtSIwx0SWrERO8U1Xicse6mXtsdd+iyMVciaSHZQ5ekRhjoktQIT7nsxPqeSpEksIcuSc0w0CWpEQa6JDXCQJekRhjoktQIr3JZQrwBSWqbPXRJaoSBLkmN6BXoSR6d5Jwk1ybZkOS5SfZKcn6S67rXPcddrCRp+/r20E8BPl9VBwHPADYAJwIXVNUK4IJuXpK0QIYGepJHAs8DTgOoqp9W1d3AUcCabrM1wNHjKlKSNFyfHvoTgM3Ax5JcnuQjSfYA9q2qWwG6133GWKckaYg+ly3uCjwLeHNVrUtyCnM4vZJkFbAKYNkyL4dbDMYxKJiXQkrj16eHvhHYWFXruvlzGAT87Un2A+heN822c1WtrqrpqpqempoaRc2SpFkMDfSqug24OcmTu0WHA9cAa4GV3bKVwLljqVCS1EvfO0XfDJyeZHfgBuANDL4Mzk5yPHATcOx4SpQk9dEr0KvqCmB6llWHj7YcSdJ8eaeoJDXCQJekRhjoktQIA12SGmGgS1IjDHRJaoSBLkmNMNAlqREGuiQ1wkCXpEYY6JLUiL6Dc0kT0XcsdsdXlx7IHrokNcJAl6RGGOiS1AgDXZIaYaBLUiO8ykUT0ffqFUnzZw9dkhphoEtSIwx0SWqEgS5JjTDQJakRva5ySXIjcC/wc2BLVU0n2Qs4C1gO3Ai8qqruGk+ZkqRh5tJDf0FVHVxV0938icAFVbUCuKCblyQtkB055XIUsKabXgMcvePlSJLmq2+gF/DFJJcmWdUt27eqbgXoXvcZR4GSpH763il6WFXdkmQf4Pwk1/Z9g+4LYBXAsmWOYS1J49Krh15Vt3Svm4BPA4cAtyfZD6B73bSdfVdX1XRVTU9NTY2maknSAwwN9CR7JHnE1mngxcBVwFpgZbfZSuDccRUpSRquzymXfYFPJ9m6/RlV9fkk3wTOTnI8cBNw7PjKlCQNMzTQq+oG4BmzLL8DOHwcRUmS5s47RSWpEQa6JDXCQJekRhjoktQIA12SGmGgS1IjDHRJaoSBLkmNMNAlqREGuiQ1wkCXpEYY6JLUCANdkhphoEtSI/o+gk4jdMa6mxa6BEkNsocuSY0w0CWpEZ5y0aLU97TVcYcuG3Ml0s7DHrokNcJAl6RGGOiS1AgDXZIaYaBLUiN6B3qSXZJcnuS8bv7xSdYluS7JWUl2H1+ZkqRh5tJDPwHYMGP+ZOADVbUCuAs4fpSFSZLmplegJzkAeBnwkW4+wAuBc7pN1gBHj6NASVI/fXvoHwTeDvyim38McHdVbenmNwL7z7ZjklVJ1idZv3nz5h0qVpK0fUMDPcnLgU1VdenMxbNsWrPtX1Wrq2q6qqanpqbmWaYkaZg+t/4fBhyZ5KXAQ4BHMuixPzrJrl0v/QDglvGVKUkaZmgPvareWVUHVNVy4NXAl6vqtcCFwDHdZiuBc8dWpSRpqB25Dv0dwFuTXM/gnPppoylJkjQfcxptsaouAi7qpm8ADhl9SZKk+fBOUUlqhIEuSY0w0CWpEQa6JDXCQJekRhjoktQIA12SGmGgS1IjDHRJaoSBLkmNMNAlqREGuiQ1wkCXpEYY6JLUCANdkhphoEtSIwx0SWqEgS5JjTDQJakRBrokNcJAl6RGGOiS1AgDXZIaMTTQkzwkySVJvpXk6iTv6ZY/Psm6JNclOSvJ7uMvV5K0PX166D8BXlhVzwAOBl6S5DnAycAHqmoFcBdw/PjKlCQNMzTQa+C+bna37q+AFwLndMvXAEePpUJJUi+9zqEn2SXJFcAm4Hzgu8DdVbWl22QjsP929l2VZH2S9Zs3bx5FzZKkWfQK9Kr6eVUdDBwAHAI8ZbbNtrPv6qqarqrpqamp+VcqSfqV5nSVS1XdDVwEPAd4dJJdu1UHALeMtjRJ0lzsOmyDJFPAz6rq7iQPBV7E4AfRC4FjgDOBlcC54yx0MThj3U0LXYKkJWxooAP7AWuS7MKgR392VZ2X5BrgzCR/B1wOnDbGOiVJQwwN9Kq6EnjmLMtvYHA+XZK0E/BOUUlqhIEuSY0w0CWpEQa6JDXCQJekRhjoktQIA12SGtHnxqIlzbs/F7e+n99xhy4b6fHmckxpVOyhS1IjDHRJaoSBLkmNMNAlqREGuiQ1wkCXpEYY6JLUCANdkhphoEtSIwx0SWqEgS5JjTDQJakRBrokNcJAl6RGDA30JAcmuTDJhiRXJzmhW75XkvOTXNe97jn+ciVJ29NnPPQtwNuq6rIkjwAuTXI+8Hrggqo6KcmJwInAO8ZXqjQ+jnuvFgztoVfVrVV1WTd9L7AB2B84CljTbbYGOHpcRUqShpvTOfQky4FnAuuAfavqVhiEPrDPqIuTJPXXO9CTPBz4JPAXVXXPHPZblWR9kvWbN2+eT42SpB56BXqS3RiE+elV9alu8e1J9uvW7wdsmm3fqlpdVdNVNT01NTWKmiVJs+hzlUuA04ANVfVPM1atBVZ20yuBc0dfniSprz5XuRwGvA74dpIrumXvAk4Czk5yPHATcOx4SpQk9TE00Kvqa0C2s/rw0ZYjSZov7xSVpEYY6JLUCANdkhphoEtSIwx0SWpEn8sWm+RgTJJaYw9dkhphoEtSIwx0SWqEgS5JjTDQJakRS/YqF2nc+l5Jddyhy8ZciZYKe+iS1AgDXZIaYaBLUiMMdElqhIEuSY3wKhepMV5ds3TZQ5ekRhjoktQIA12SGuE5dGmRcAx/DWMPXZIaMTTQk3w0yaYkV81YtleS85Nc173uOd4yJUnD9Omhfxx4yTbLTgQuqKoVwAXdvCRpAQ0N9Kr6CnDnNouPAtZ002uAo0dclyRpjuZ7Dn3fqroVoHvdZ3QlSZLmY+xXuSRZBawCWLbMO9OkbXn1ikZlvj3025PsB9C9btrehlW1uqqmq2p6ampqnm8nSRpmvoG+FljZTa8Ezh1NOZKk+epz2eIngP8CnpxkY5LjgZOAI5JcBxzRzUuSFtDQc+hV9ZrtrDp8xLVIknaAd4pKUiOaG8vFKwakfhw3vT320CWpEQa6JDXCQJekRhjoktQIA12SGmGgS1IjDHRJaoSBLkmNMNAlqRHN3SkqaefnXarjYQ9dkhphoEtSIwx0SWqEgS5JjTDQJakRXuUi6VfyGQOLhz10SWqEgS5JjTDQJakRBrokNcJAl6RG7FCgJ3lJkv9Ocn2SE0dVlCRp7uZ92WKSXYBTgSOAjcA3k6ytqmtGVdxMXjolLT07+yBeO1t9O9JDPwS4vqpuqKqfAmcCR42mLEnSXO1IoO8P3DxjfmO3TJK0AHbkTtHMsqwesFGyCljVzd6X5A7g+zvwvovZ3izNti/VdoNtn0jbXzuJN5mb/9f2EdT3uD4b7UigbwQOnDF/AHDLthtV1Wpg9db5JOuranoH3nfRWqptX6rtBttu2ydrR065fBNYkeTxSXYHXg2sHU1ZkqS5mncPvaq2JHkT8AVgF+CjVXX1yCqTJM3JDo22WFWfAz43x91WD9+kWUu17Uu13WDbl6oFaXuqHvA7piRpEfLWf0lqxNgCfdiwAEkenOSsbv26JMvHVcsk9Wj385JclmRLkmMWosZx6dH2tya5JsmVSS5I0utSrMWgR9v/JMm3k1yR5GtJnroQdY5D3yFAkhyTpJI0ceVLj8/89Uk2d5/5FUn+cOxFVdXI/xj8SPpd4AnA7sC3gKdus82fAR/upl8NnDWOWib517Pdy4GnA/8OHLPQNU+47S8AHtZN/2kLn/kc2v7IGdNHAp9f6Lon1fZuu0cAXwG+AUwvdN0T+sxfD3xoknWNq4feZ1iAo4A13fQ5wOFJZrtZaTEZ2u6qurGqrgR+sRAFjlGftl9YVT/qZr/B4N6FFvRp+z0zZvdglpvwFqm+Q4C8F/hH4MeTLG6MdsqhT8YV6H2GBbh/m6raAvwAeMyY6pmUpTwcwlzbfjzwn2OtaHJ6tT3Jnyf5LoNge8uEahu3oW1P8kzgwKo6b5KFjVnff++v7E4xnpPkwFnWj9S4Ar3PsAC9hg5YZFpsU1+9257kD4Bp4P1jrWhyerW9qk6tqicC7wD+auxVTcavbHuSBwEfAN42sYomo89n/hlgeVU9HfgSvzwjMTbjCvQ+wwLcv02SXYFHAXeOqZ5J6TUcQqN6tT3Ji4B3A0dW1U8mVNu4zfVzPxM4eqwVTc6wtj8C+A3goiQ3As8B1jbww+jQz7yq7pjxb/zfgN8cd1HjCvQ+wwKsBVZ208cAX67ul4RFbCkPhzC07d3/ev8rgzDftAA1jkuftq+YMfsy4LoJ1jdOv7LtVfWDqtq7qpZX1XIGv50cWVXrF6bckenzme83Y/ZIYMPYqxrjr8AvBb7D4Jfgd3fL/pbBhwnwEOA/gOuBS4AnLPQv1xNq97MZfLv/ELgDuHqha55g278E3A5c0f2tXeiaJ9j2U4Cru3ZfCDxtoWueVNu32fYiGrjKpedn/g/dZ/6t7jM/aNw1eaeoJDXCO0UlqREGuiQ1wkCXpEYY6JLUCANdkhphoGtRSXJfkifMc9+LJjLiXU/daHxfW+g61I4demKRNGlV9fCFrkHaWdlDl6RGGOjaKSR5Q5LPzJi/PsnZM+ZvTnJw94CEJ3XLPp7k1CSfTXJv96CUJ87Y54gk1yb5QZIPMWNApSRPSnJxt+77Sc6asa6SvCXJDd2693eDTG1d/8YkG5LcleQLMx/UkeSgJOcnubN7+MGrZqx7TJK1Se5Jcglwf63SKBjo2llcDPx2kgd1Y2DsBhwG0J0zfzhw5Sz7vQZ4D7Ang2Ek3tftszfwSQajGu7N4Pbsw2bs917gi91+BwD/vM1xf5/BiJDPYjDO9Ru74x4NvAt4BTAFfBX4RLduD+B84Axgn662f0nytO6YpzIYD3y/7nhv7P+fRxrOQNdOoapuAO4FDgaeD3wB+N8kB3XzX62q2R4K8qmquqQGY+qf3u0Pg3E2rqmqc6rqZ8AHgdtm7Pcz4HHAY6vqx1W17Y+TJ1fVnVV1U7fva7rlfwz8Q1Vt6N7z74GDu176y4Ebq+pjVbWlqi5j8KVyTJJdgFcCf11VP6yqq5jAcKpaWgx07UwuBn4HeF43fRGDMH9+Nz+bmSH9IwY9eYDHMuMBBDUYtGjmAwnezuAUzCVJrk6ybW955rbf644Hgy+BU5LcneRuBkM+h8HDDR4HHLp1Xbf+tcCvMejN7zrLcaWR8SoX7UwuBn4PeDyDnu/WQHwu8KE5HutWZoxX3T3e8P75qroN+KNu3W8BX0rylaq6vtvkQAYj5QEs45djXd8MvK+qTt/2Dbte+sVVdcQs63YBtnTHvXbGcaWRsYeuncnFDB4k/dCq2sjg/PRLGDya8PI5HuuzwNOSvKJ7gMpbGPSUAUhybJKtzzS9i8HTZn4+Y/+/TLJn99iwE4CtP5p+GHjn1vPiSR6V5Nhu3XnAryd5XZLdur9nJ3lKVf0c+BTwN0keluSp/PJ5ANJIGOjaaVTVd4D7GAQ5NXiw8g3A17tAnMuxvg8cC5zEYNz5FcDXZ2zybGBdkvsYPJjghKr6nxnrzwUuZTB++WeB07rjfho4GTgzyT3AVcDvduvuBV7M4GEHtzA4HXQy8ODumG9icEroNuDjwMfm0iZpGMdDl7aRpIAVM06/SIuCPXRJaoSBLkmN8JSLJDXCHrokNcJAl6RGGOiS1AgDXZIaYaBLUiMMdElqxP8BrbEE9poXYggAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.windspeed.values, bins=30, kde=False)\n",
    "plt.xlabel('windspeed', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "两两特征之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get the names of all the columns\n",
    "cols=data.columns \n",
    "\n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "data_corr = data.corr().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15, 15)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "plt.savefig('Tab 1.png' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "weathersit and temp = 0.99\n",
      "casual and registered = 0.95\n",
      "instant and season = 0.87\n",
      "dteday and yr = 0.83\n",
      "windspeed and registered = 0.67\n",
      "instant and casual = 0.66\n",
      "temp and registered = 0.63\n",
      "instant and registered = 0.63\n",
      "weathersit and registered = 0.63\n",
      "season and casual = 0.59\n",
      "workingday and atemp = 0.59\n",
      "season and registered = 0.57\n",
      "temp and casual = 0.54\n",
      "temp and windspeed = 0.54\n",
      "weathersit and windspeed = 0.54\n",
      "weathersit and casual = 0.54\n",
      "weekday and windspeed = 0.52\n"
     ]
    }
   ],
   "source": [
    "#Set the threshold to select only highly correlated attributes\n",
    "threshold = 0.5\n",
    "# List of pairs along with correlation above threshold\n",
    "corr_list = []\n",
    "#size = data.shape[1]\n",
    "size = data_corr.shape[0]\n",
    "\n",
    "#Search for the highly correlated pairs\n",
    "for i in range(0, size): #for 'size' features\n",
    "    for j in range(i+1,size): #avoid repetition\n",
    "        if (data_corr.iloc[i,j] >= threshold and data_corr.iloc[i,j] < 1) or (data_corr.iloc[i,j] < 0 and data_corr.iloc[i,j] <= -threshold):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j]) #store correlation and columns index\n",
    "\n",
    "#Sort to show higher ones first            \n",
    "s_corr_list = sorted(corr_list,key=lambda x: -abs(x[0]))\n",
    "\n",
    "#Print correlations and column names\n",
    "for v,i,j in s_corr_list:\n",
    "    print (\"%s and %s = %.2f\" % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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bQypXA6qBt/SNrwZOuRp0emgiIh0TOIPNSwey7K7bsDPSLLvEBaTAfZTUxmNrL01EZCIpy64D4tA3XkQkbuLQvDRxT+E49I0XEYmbTMratp9Q6aAQxaFvvIhI3NQC54VXi3zxo4uY3JXhSKnGcy8dpnDSlMjGkLjHcBz6xouIxE1XNs3J0wp84itbmXfjJj7xla2cPK1AV4QN+hIXkOLQN15EJG76q/W2H9b7q9G1nwg1IJnZ+Wa228z2mNmnR7nmw2b2jJntMrOvhjkeiEd5DBGRuInDh/XQApKZpYE7gQuAdwErzOxdw66ZC9wA/Ia7nwFcHdZ4BmSbG3dDa9k19pDUfkJEkisOH9bDDH1LgD3uvhfAzHqBC4FnhlxzBXCnu78C4O4/D3E8AOSyaZ75ycGWjbtt+w5xzryTwv7VIiKxlRslyy53nGTZnQzsH/L6APC+YdfMAzCz7wNpYK27fzPEMVGq1nnHSVP4xFe2tpTHKFXrFHLaRxKRZKoGTu8T+1q6afc+sY/Lzz6NfERjCPMJ3C6sDk9lywBzgd8CZgHfNbN3u/urLT/IbBWwCmD27NnjGlQQ+GB5DGCwPMY9KxeN6+eKiBzLCvkMd3x7D7d968eD72VSxlXnzo1sDGEmNRwAThnyehbwszbXfMPdq+7+E2A3jQDVwt3vdvfF7r545syZ4xqUKjWIiIxULNdHqdRwfGTZPQnMNbPTzCwH9AAbh13zMPDbAGZ2Io0lvL0hjikWN11EJG5SBrcsn9+S8HXL8vlEme8V2rTA3WtmdhWwmcb+0JfcfZeZfQbY4u4bm9/7PTN7BqgD17n7wbDGBI2b/jeXLhjRoE9JdiKSdFO6MiP6IUUpcR1ja7WAQ/0V1qwfkkmyYgHTu3NkMok7JywiAoT+bBxTaEvcE7i/VmfN+mGnkdfvoL+mJTsRSa7+Wp3exxtZdrv/4gLWLjuD3sf3RfpsTNxOfhxOI4uIxE0hl+aihbO4/sGjHWNvvmQ+hQi7aSduhhSHnh8iInFTrNS5/sHWjrHXP7iTYuX4yLKLpZTZKJkkymoQkeSKw+pR4gJSVy7NrZt3t6yT3rp5N10RTktFROImDkdiErdx0leu8eJrZc67/dHB95bOmUFfucaUrmwHRyYi0jmZFKN0jI1uDImbIaVHWbJLa8lORBKsNqSW3WCW3RP7qEXYvDRxM6SuXJpbv767pYDgrZt3c9tHFnR6aCIiHXO817KLpb5yjTknTmp5b86Jk9SgT0QSLQ4ZyIkLSN3ZND1LZrN24y5Ov2kTazfuomfJbLoj7BsvIhI3cchATlxAikPfeBGRuOnKpfnnH73IXZedxbOfvYC7LjuLf/7Ri5FmICduDykOufYiInFTqtQ5951v5cr7trU2L63UI2vPk7gZUhxy7UVE4ibwo81LB1aPrtuwkyDCAtyJC0iFXJo7VixoWSe9Y8WCSOs1iYjETRyalyZynao7m27p+ZFRMyQRSbi+ZpbdY3uPtqR776nTIy0akLgZUqlW57VSjSvv28a8Gzdx5X3beK1Uo6T2EyKSYIVcmpsvac2yi7rad+JmSEHgXPPAU4OfAh7be5BrHniKe1Yu6vDIREQ6p1ips+tnr7asHj323MucMGkmU7qimbskboYUh3VSEZG4yaeMpb96Iq8Wq7jDq8UqS3/1RPIRbmkkLiD1jXIaWZUaRCTJag61IGh9LwioRZdkl7wlu0IuzR09C+ir1DlleoH9h4pMyqWVZSci0mGJC0jlakA1cG546OnBw1+f//CZlKsBhXziJowiIoNK1aDl2XjL8vkUIuzKk7gncN2PJjUMHP665oGnqEd4+EtEJG4CZ5SDsdGNIXEzJJUOEhEZqZBP89apeTZffc5ga567HtlDIR/ddkbiZkhxKLEuIhI3pUqdmz70TvLNFrH5TIqbPvROSpXozmgmLiDFocS6iEgcDewhnX7TJm546GlK1eCN/9IESlxA6sqluXXz7pY2vbdu3h1piXURkbjRHlIHFMt1XnytzHm3Pzr43tI5MyiW60zuStztEBEB4rGHZH6MZZctXrzYt2zZ8qb/frFS49VilWseeKol7XtaIUshp4AkIslULNc4VKxw3YadLWnf0wu5iahkM6Y9kcQFpHoQcKRUw2GwXpMBk7sypFOJW8EUEQHgcKnKqnu3tlT7XjpnBnevXDQR1b7HFJAS9wRuHIwNWuo1VYOAcsSbdyIicRKHIzGJC0jQ+UwSEZG4iUOdz8QFpDhkkoiIxE0+Zazrae2mva5nQaTVvhO3i1/Ip0dpP6G0bxFJrnLg9D6xj7XLzhjMsut9Yh9/cPZp5CIaQ+ICUnGUNr3Fco3JEbXpFRGJm0n5DHd8ew+3fevHg+9lUsZV586NbAyJW7JTpQYRkZGO+z0kMzvfzHab2R4z+3Sb73/czF4ysx3Nf/7vMMcDqtQgItJOdybddg+pOxPdszG0JTszSwN3Ah8ADgBPmtlGd39m2KX3u/tVYY1jOFVqEBEZqb9WH3UPaUommsW0MJ/AS4A97r4XwMx6gQuB4QEpUimDW5bPH3EaOcJEEhGR2InDHlKYAelkYP+Q1weA97W57hIzOwd4Fviku+9vc82E6sqm+NzF7xlsYd6VTdxWmohIi75REr76yrWJqNQwJmE+idvNOYaf9vlfwKnuPh/4FvDltj/IbJWZbTGzLS+99NK4BpXPpsimUkwrZDGDaYUs2VSKvIKSiCRYHM4hhVbLzsyWAmvd/bzm6xsA3P1zo1yfBg65+1te7+eOu7hqucar/W2Kq3ZnJ6KAoIjIMalUqVELnFrgg3U+MykjkzK6xl94ekxRLcwn8JPAXDM7DXgB6AEuHXqBmb3N3f+9+XIZ8KMQxwNA4M7Xtuxv2bj72pb9XH72aWH/ahGR2KoGPmpx1a6IxjDmgGRmZwFn01h2+767b3u96929ZmZXAZuBNPAld99lZp8Btrj7RmC1mS0DasAh4ONv7l9j7LpzaS5aOIvrHzya1HDzJfPpVtq3iCRYHIqrjmnJzsz+FFgOPNR86yJgg7v/RYhja2u8S3Yhl1gXETkmHS5V+fvv/YTz3v22wdWjzT/890bad0TtJ8Ya+lYAC929BGBmfwVsAyIPSOMVh08BIiJxk08ZPUtms6Z3x+DqUdRJDWNNLXseWpYR88BzEz6aCMShPIaISNyUA2dN746WTghrendQjrAVwlinBWVgl5n9Hxp7SB8AvmdmdwC4++qQxjfhujNp7rrsLF4tVgfPIU0rZCMtjyEiEjdxWD0a62/6evOfAY9M/FCiUQkCyrVGg76BaentPQvIZQIyyas1KyICxONgbGjnkMIy3qSGI6UqV7RJarhn5SK1nxCRxCpVarxWqo3YQ5ralYnXOSQz+xDw58Dbm3/HAHf3qW96eB1SGGVaqkOxIpJkuWyal146wt0rFzEpn6GvXGPfwT5OnPK6tQom1FjXqG4HPgbMcPep7j7lWAxG0Kj23S6poViud2hEIiKdV6nWmTmli1X3bmXejZtYde9WZk7polKN7tk41oC0H/ihH2vre21kUrSt1xRRdXURkViqjpJlV41hlt1/Bf7JzP6FRsYdAO5+WyijClFtlL7xKh0kIkl2LGXZfRY4QuMsUi684YSvEIOeHyIicROHLLuxBqTp7v57oY4kIgN7SMNvujrGikiS5ZrtJ4Zn2eViWKnhW2Z2XASklMHnP3xmyx7S5z98pjrGikiiVQNn608PcddlZ/HsZy/grsvOYutPD0W6hzTW4qqHgUlApflPx9K+x3sOqVyp0V8L2lRqSJEff669iMgxqR4EvPBKaUQnhJNP6CKdGnfW18SdQ3L3KeMbS3xUAufK+7a1rfad7+C4REQ6qVipc/2DOwefjY/tPcj1D+5sdkKIJg15TL/FGi4zs//WfH2KmS0Jd2jhiEMmiYhI3MTh2TjWsPe3wFKOdnw9AtwZyohCpmrfIiIjxeHZONaA9D53/2OgBODur3CMpn8XcmluvmR+S1LDzZfMp6COsSKSYHF4No51LlY1szSN1hOY2UwgCG1UIeqvBDy8/UDLwdiHtx/g8rPnMDmidVIRkbgpVuptn42NjrHRPBvHGpDuoNF+4iQz+yzw+8B/C21UIUoZXLxoFtdtOJpJcsvy+Ur7FpFES5vx0aWn8ov+KgD5TIqPLj2VtEX3cBxrlt0/mNlW4Fwa6XsXufuPQh1ZiKZ2ZbjrsrOY2p3ltf6qgpGIJF4uk+JIpdbSK27digVMycSsdJCZfcXdPwr8W5v3jim5TIojfSN7fkyfpCw7EUmu/mqd3seH1fl8fF9jyS4do7Rv4IyhL8wsAyya+OGEr79ab1vRtj/CEusiInFTyKW5aOEs1m7cxek3bWLtxl1ctHBWpEkNrxuQzOyGZpWG+Wb22sA/wIvANyIZ4QSLQ669iEjcDD0YO/Bh/foHd1KsxKQfkrt/rlml4RYa3WI/APwn4GJgU/jDm3hq0CciMlIcPqyP9TftBR4FZgE7gF8DHgN+J6RxhSaVgr+5dAFHSvXBWnaTu9KMv1STiMixqzhK+4liucbkiNpPjPUxvBp4L/BTd/9tYCHwUmijClE+k6JcdW546GlOv2kTNzz0NOWqk1fLWBFJsJQZtyxvPRjbOBITs7RvoOTuJTPDzPLu/m9mdnqoIwtJsVLnwa37WzJJHty6P9LDXyIicdOVS3Pr13e3PBtv3byb2z6yILIxjDUgHTCzacDDwP8xs1eAn4U3rPAUcmkuWXQK1254ajDt+9blZ6p0kIgkWl+5xouvlTnv9kcH31s6Z0akHWPH1A+p5S+Y/SbwFuCb7l4JZVSvY7z9kA6Xqqy6d2vb9hNR3XQRkbgpVWq8Vq6xZv2OloOxU/MZusbfK27i+iEN5e7/8suPJT7ikEkiIhI32UyKSZ7mix9dxOSuDEdKNdKpxvtRSdymidK+RURGKlcDDpfqfOIrW5l34yY+8ZWtHC7VKVejq6OduGlByuCW5fNVXFVEZIjAne37DrXU+XzsuZd5/9yZkY0hcQEJoCub4nMXv2fwHFJXNnETRRGRFl3ZNIvePp0r79vWUuezKxuT0kEiIpIMcajzmbiAlDLIDCvLkEmltGQnIokWh4SvUAOSmZ1vZrvNbI+Zffp1rvt9M3MzWxzmeABymTSZlDGtkMUMphWyZFJGLqNzSCKSXH3N0kFDvffU6fSVa5GNIbSA1Gx5fidwAfAuYIWZvavNdVNolCZ6PKyxDJVKGYVchkyzv0cmnaKQy5DSFElEEqw7m2Zdz4KW0kHrehbQHeEeUphzsSXAHnffC2BmvcCFwDPDrvtz4K+Ba0McS4tUypjcnIZO1vkjEZFGg74nhjXoeyLaBn1hPo1PBvYPeX0AeN/QC8xsIXCKu/+jmY0akMxsFbAKYPbs2eMeWBA4xWqdQi5NsVKnkE1rhiQiiTYpn+GOb+/htm/9ePC9TMq46ty5kY0hzLDX7gk/WKfIzFLAF4Br3ugHufvd7r7Y3RfPnDm+nPggcA72lbniy1uYd+MmrvjyFg72lQmCX66EkojI8SQOe0hhzpAOAKcMeT2L1oKsU4B3A49Yo7z5fwA2mtkyd3/zxereQLFSY8vz7Q9/RdXzQ0Qkbgb2kNb07mg5h3S87CE9Ccw1s9OAF4Ae4NKBb7r7L4ATB16b2SPAtWEGI4jH4S8Rkbjpr9bZ+tORH9bPnjszsj2k0H6Lu9eAq4DNwI+AB9x9l5l9xsyWhfV730gcDn+JiMRNIZfmjF+ZxpX3bWPejZu48r5tnPEr0yJtzfNLt5/otPG2nwjcmXfjJmpD9owyKePZz14QaWdEEZE4Cbk1TzjtJ451faP0jY+yCZWISNxMymd469Q8m68+ZzDt+65H9hw/lRriKJuytoe/skr7FpEEK1Xq3PShd5Jv9j/KZ1Lc9KF3UqpEt52RuBkSNNZKh27cZRSMREQoVQNueOjpltY8hQgXjhI3Q6oGzpe+9xNefK2MO7z4Wpkvfe8nVHUOSUQSLHC4bsPOloSv6zbsJMpHY+JmSHE4jSwiEjeFfLptte9C/vg4hxRLxXKd1b/zDs5799sGN+42//DfKZbrTO5K3O0QEQGgOErCV7Fci6xoQOJClec2AAAYrElEQVSW7DIp6Fkym7Ubd3H6TZtYu3EXPUtmk0ncnRAROSplxuc/fGZLwtfnP3xmpMdhEncOKeRcexGRY1KxXKMaBLgzmPBlBtlUisL4U791DqmdOHRFFBGJm3w2xSu/qHLthqcGs+xuXX4m/+EtOocUmuIoFW2LEVa0FRGJm2KlzrUbnmrJsrt2w1MUIzyHlLiApIOxIiIjxWH1KHHrVJXAR+2KmO/04EREOqRYro+SZRddBnLikhpUXFVEZKRypcYvSrUR/ZDe0pUhn1NSQyhUXFVEZKQ4rB4lboZUqwUcKlZGfAqYXsiR0WEkEUmokFePNENqp79WH/VTwBQFJBFJqL5yrW0VmyhXjxIXkFTLTkRkpFzK6Fkye8TqUS7CDOTEBaQ4ZJKIiMRNNaDt6tHlZ8+JbA8pcU/glMH/c+lCDpdqnDK9wP5DRaZ0ZdAxJBFJsu5ciuXvPYVP3X+0UsNtHzmT7lx0WxmJ2zRJG9TdueGhpzn9pk3c8NDT1N1JKyCJSIIVK3U+dX9rpYZP3a9KDaGqBM6a9Ttabvqa9TuoqEGfiCTYpHyGt07Ns/nqc3juLz/I5qvP4a1T86rUEKY4lMcQEYmbUqXOteedznUbdra0MC9V6hNR7XtMEjdDGkhqGGogqUFEJKnq7m1bmNcjPKuauICUMrhl+fyW4qq3LJ+vpAYRSbQ4rB4lb53KoDub5nMXv2cwy647mx7jOWIRkeNTHMqqJW6GlM+kCIYlMASBk1eVBhFJsEIuze3DWvPc3rOAQi4d2RgSN0MqVuqs7t0xSgtzBSURSaZaLWBSLs1dl5012MI8kzJqtYB0RGeREheQ4rBOKiISN3WHV/urI7LsphdykY0hcU/hYrnetoCgSgeJSJIFzmCWHTCYZXfPysWRjSFxT+BMirYFBLWFJCJJVsin264eFfLR7SEl7jFcDZw1vcMqNfTuoKpKDSKSYMVmlt1QjTOatcjGkLiApD0kEZGRukfJsutWll144pBrLyISN+VqQFc21ZJlZ9Z4v5CPZu6SuBlSNmWsG/YpYF3PArIq1SAiCXe4VOPK+7Yx78ZNXHnfNg6XoluuAzCPsE7RRFi8eLFv2bLlTf/9wJ1Hn/05Z82ezuSuDEdKNbbtO8Q5806aiL7xIiLHpCOlGlfcu2XEGc17Vi6eiAzkMT1cQ12yM7PzgXVAGvg7d/+rYd//L8AfA3XgCLDK3Z8Jc0ylSp13nDSFT3xla8cq2oqIxE0hnx5sPzFwJOauR/ZEmmUX2gzJzNLAs8AHgAPAk8CKoQHHzKa6+2vNr5cBf+Tu57/ezx3vDOlwqcqqe7eOUqlBe0gikkzFco3XSjU+ef/RIzFf+MgCpnZlJuLD+phmSGHuIS0B9rj7XnevAL3AhUMvGAhGTZOA0NcPlWUnIjJS4M4n7289EvPJ+3cQRLitE+ZT+GRg/5DXB4D3Db/IzP4Y+BSQA36n3Q8ys1XAKoDZs2ePa1B95VrbSg3KshORJCuM8mE9yq2MMGdI7aZoI0Ktu9/p7r8KXA/c1O4Hufvd7r7Y3RfPnDlzXIPqzqbpWTKbtRt3cfpNm1i7cRc9S2Y3WlCIiCTU8X4w9gBwypDXs4Cfvc71vcBFIY4HgP5qvW2lhv6qOsaKSHKlzEZpXhpd9nGYc7EngblmdhrwAtADXDr0AjOb6+4/br78v4AfEzLtIYmIjNSVS3Pr13ezdtkZg9sZt27ezW0fWRDZGEJ7Crt7zcyuAjbTSPv+krvvMrPPAFvcfSNwlZn9LlAFXgE+FtZ4BhTL9baVGlTtW0SSrK9c48XXypx3+6OD7y2dMyPS/fXEHYwtVWq8Vq6xZv2Qat8rFjA1n6Erp4AkIslUqwcc6quM6IQwfVKOTHrcuzudPxgbR4E32pgPr9ekYt8ikmSlap2tPz3U8mx87LmXef/cmUwef0Aak8QFJIBqPeBIqc6UriyvFqtM7kqTTSWurJ+IyKCUGe+ZNY0r79vWUsXmeElqiK1SNeCGh55uuekFHUESkQQ7rpMa4ioObXpFROImDkkNiVunikObXhGRuIlDa57EzZDUoE9EZKRcNs2mLftbkhq+seMFPrr01MjGkLiA1J1Ns65nwYjURpUOEpEk6yvX+OYPX+TPNh7tALR0zgwuPmuWluzC0l+t0/vEPtYuO4Pdf3EBa5edQe8T+1Q6SEQSrTuTbrtk152J7sN64mZIk/IZ7vj2Hm771tEqRZmUcdW5czs4KhGRzuqvtT+HdPbcmUzJ6BxSKIrletv2EyodJCJJVsilWfz26bxarA6e0Vz89ukUcpohhSaTgp73zR5ROiiiDwAiIrFUrgZUA285o/n5D59JuRpQyEfzgEzcY7gaOGvWD2s/sX4HVdUOEpEEC9z52pb9LfvrX9uy/7jpGBtLaj8hIjJSdy7NRQtncf2DOwdnSDdfMp/uCJfsEjdDGmg/MdRA+wkRkaQqVupc/+DOltWj6x/cSbES3bMxcQEpZYzSFbHTIxMR6Zw4rB4lbp0qZTA5n+FzF7+HU6YX2H+oyOR8RgFJRBItDlVsEjdDqgbOvf/6POVaAEC5FnDvvz6vpAYRSbRsyli3YtjB2BWqZReqSfkMe1/ua3lv78t9SmoQkUTLZlJM9gx3r1zEpHyGvnKNtBnZCM/EJO4pXKrUufa807luw86WfkilSp2CgpKIJFS1FnCkXBtR5zNlGdI5nUMKRd19sB/SQCbJdRt2Uo8w115EJG6qgbOmd9gZzd5oz2gmLiDFIZNERCRu4vBsTNxTuK9ca1vLTv2QRCTJlGXXAd3ZND1LZrN24y5Ov2kTazfuomfJbPVDEpFEi0PHWPNjbO9k8eLFvmXLljf99w+Xqqy6d2vLp4Clc2Zw98pFmiGJSGLVg4BKLaAW+GCWXSZl5DIp0qlxz13GFNUSt2QXh3VSEZG4qdUCDpdGZtm9pSu6LLvEPYXjsE4qIhI3lcAHu2kP7K/3PrGPPzj7NPIRjSFxe0iFXJqbL2mtZXfzJfMjbUIlIhI3hWa176H76xctnBXpszFxAam/GvDw9gMtPT8e3n6A/mrQ6aGJiHRMHKp9J27JrpBNs+J9b2f1+u2D66R3rFhIQVl2IpJgcdhfT1xASqWMGZNy3POxxRRyaYqVOoVsmpTKfYtIgg30ihu+v14s15ncFU2oSNySHYC7M5DuPvRrEZGkikOvuMTNkOr1gIN9lRGpjTMm5UinExmfRURi0SsucU/gYrXetoBgsaoW5iKSXLlsmm/seIFphSxmMK2Q5Rs7XiAX4f564mZIcdi4ExGJm75yjW/+8EX+bOMzg+8tnTODi8+adXzUsjOz881st5ntMbNPt/n+p8zsGTPbaWb/bGZvD3M8cPRg7FADB2NFRJKqkEtz6/IzW/aQbl1+ZqTnkEKrZWdmaeBZ4APAAeBJYIW7PzPkmt8GHnf3opldCfyWu3/k9X7ueGvZaQ9JRGSkYrlGNQhwh6ndWV7rr2IG2VRqIpqXdryW3RJgj7vvBTCzXuBCYDAguft3hlz/A+CyEMcDQDqdYsakXEub3kI2rWAkIonXV65zzQNPDX5Y//yHz2Rad3TPxjB/08nA/iGvDzTfG80fAptCHM+gdDrFlK4sKTOmdGUVjEQk8QJ3rnngqZaEr2seeIogwmMxYc6Q2k3R2v6bmdllwGLgN0f5/ipgFcDs2bMnanwiItJUGCXhawKW68YszKnBAeCUIa9nAT8bfpGZ/S5wI7DM3cvtfpC73+3ui9198cyZM8c9sCBwjpRrBN78M8Ke8SIicTRQqWGogUoNUQkz9D0JzDWz04AXgB7g0qEXmNlC4IvA+e7+8xDHMigInIN9lRG17GZMyql8kIgkVsrgby5dwJFS/ejB2K708XEw1t1rwFXAZuBHwAPuvsvMPmNmy5qX3QJMBjaY2Q4z2xjWeAYUq3VWr9/esk66ev12HYwVkURLGwQONzz0NKfftIkbHnqawBvvRyVxLcwDd+bduInakGW6TMp49rMXkDLNkEQkmQ6Xqqy6d2tLcdWlc2Zw98pFE3EwdkwP18SllxUro6yTRtjzQ0QkbuJQxSZxAak7k2Jdz4KW08jrehbQnUncrRARGRSHpIbEPYX7a8Fg3/iBjrG9T+yjv6aOsSKSXGo/0QGFXJq9L/e1vLf35b5I6zWJiMRNLp1q234iF2HhgMTNkEqVOteedzprN+7i9Js2sXbjLq4973RK2kMSkQQr1QPu/dfnKTdXi8q1xutSPbrVo8Rl2R0pVbmiTSbJPSsXMTmiEusiInETcgaysuzaiUN5DBGRuIlDBnLiAlIcMklEROKmkE1zx4qFLUkNd6xYSCHCjrGJW7JrlA4qs3r9jiGlgxYwY1JepYNEJNGCwClW6xRyaYqVOoVseqKeix3vhxRLqZRxQndrP6TuzITddBGRY1YqZUxubl9M7sA2RuICUq0WcKg4smPs9EKOjA7HikiChThDGpPEPYH7a3XW9O5oKa66pncH/TXtIYlIcgWBc7hU5eXDZdzh5cNlDpeqkbbnSdwMKQ71mkRE4qZUq3O4XOOGh54eXD26Zfl8spkUhVw0z8fEzZD6yrW2WXZ95VqHRiQi0nlBANdt2NmyenTdhp0EEVZVS1xA6s6kRymuqtJBIpJchXyat07Ns/nqc3juLz/I5qvP4a1T8xTySvse1XjTvqGR2NBfq7dk2SmhQUSSrFiucahY4boNO1uW7KYXchNROECVGkaTyaSY0pUlZcaUrqyCkYgkXt297ZJdPcJJi57EIiISi4QvBSQREYlFwpcCkoiIkDZr26AvPf5K32OmwzciIkJXLs2tX9/N2mVn8I6TJrPn50e4dfNubvvIgsjGoIAkIiIUK3VefK3Mebc/Ovje0jkzKFbqkdW105KdiIjEov2EZkgiIkIqZcyYlOOejy3uWHFVBSQREQE6335CS3YiIgI0Kn4fKdcIvPlnhJW+QTMkERFhoJt2hdXrtw/ppr2QGZNykS3baYYkIiIUq3VWr9/eUjpo9frtFKvR9YrTDElERCjkjlb7HjiHdNcjeyjklGUXqk636RURiZtSpc61550+otp3qVKfiGrfY5K4JbuBddIrvryFeTdu4oovb+FgXyXyzTsRkThRte8OiMM6qYhI3KjadwcUcum2Nz3KdVIRkbhRte8OKFbqbW96saIZkogkVyGbZl3PgpbSQet6FkRaOihxLczjkGsvIhJH9XpAsVpnUj5DX7lGIZsmnZ6QecuYHq6hLg6a2fnAOiAN/J27/9Ww758D3A7MB3rc/WthjgcapTGmF7LcvXJRy01XMBKRpEunU0xpBqApXdnIf39oS3ZmlgbuBC4A3gWsMLN3DbtsH/Bx4KthjWO4IHAOFausuncr827cxKp7t3KoWFWWnYhIh4W5h7QE2OPue929AvQCFw69wN2fd/edQBDiOFooy05EJJ7CDEgnA/uHvD7QfK+jlGUnIhJPYQakdpsyb2pdzMxWmdkWM9vy0ksvjWtQcUhtFBGRkcIMSAeAU4a8ngX87M38IHe/290Xu/vimTNnjmtQhVyamy+Z35LaePMl8zVDEhHpsDCz7J4E5prZacALQA9waYi/b0z6qwEPbz/A2mVnDBYQfHj7AS5//xwm5xN3LEtEJDZCC0juXjOzq4DNNNK+v+Tuu8zsM8AWd99oZu8Fvg6cAPwnM/vv7n5GWGOCxuGvFe97+4hzSFEe/hIRkZESdzAWVO1bRCRinT8YG1ed7hsvIiIjJXLTpNN940VEZKTETQ9Uy05EJJ4SN0NSpQYRkXhKXEBSpQYRkXhKXEBSPyQRkXhKXEAqZNPcsWJhS6UGnUMSEem8xCU1pFLGjEk57vnYYp1DEhGJkcQFJNA5JBGROErckp2IiMSTApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCApKIiMSCuXunx/BLMbOXgJ9O0I87EXh5gn7WsUz3QfdggO6D7gFM/D142d3Pf6OLjrmANJHMbIu7L+70ODpN90H3YIDug+4BdO4eaMlORERiQQFJRERiIekB6e5ODyAmdB90DwboPugeQIfuQaL3kEREJD6SPkMSEZGYSERAMrPzzWy3me0xs0+3+X7ezO5vfv9xMzs1+lGGawz34FNm9oyZ7TSzfzazt3dinGF7o/sw5LrfNzM3s+Mu22os98DMPtz872GXmX016jFGYQz/T8w2s++Y2fbm/xcf7MQ4w2RmXzKzn5vZD0f5vpnZHc17tNPMzgp1QO5+XP8DpIHngDlADngKeNewa/4I+B/Nr3uA+zs97g7cg98GCs2vrzze7sFY70PzuinAo8APgMWdHncH/luYC2wHTmi+PqnT4+7QfbgbuLL59buA5zs97hDuwznAWcAPR/n+B4FNgAG/Bjwe5niSMENaAuxx973uXgF6gQuHXXMh8OXm118DzjUzi3CMYXvDe+Du33H3YvPlD4BZEY8xCmP5bwHgz4G/BkpRDi4iY7kHVwB3uvsrAO7+84jHGIWx3AcHpja/fgvwswjHFwl3fxQ49DqXXAjc6w0/AKaZ2dvCGk8SAtLJwP4hrw8032t7jbvXgF8AMyIZXTTGcg+G+kMan4qON294H8xsIXCKu/9jlAOL0Fj+W5gHzDOz75vZD8zsDU/YH4PGch/WApeZ2QHgn4A/iWZosfLLPjvGJRPWD46RdjOd4amFY7nmWDbmfz8zuwxYDPxmqCPqjNe9D2aWAr4AfDyqAXXAWP5byNBYtvstGjPl75rZu9391ZDHFqWx3IcVwP9098+b2VLgK837EIQ/vNiI9NmYhBnSAeCUIa9nMXLqPXiNmWVoTM9fbxp7rBnLPcDMfhe4EVjm7uWIxhalN7oPU4B3A4+Y2fM01sw3HmeJDWP9/+Eb7l51958Au2kEqOPJWO7DHwIPALj7Y0AXjRpvSTKmZ8dESUJAehKYa2anmVmORtLCxmHXbAQ+1vz694Fve3NH7zjxhveguVT1RRrB6HjcM4A3uA/u/gt3P9HdT3X3U2nspS1z9y2dGW4oxvL/w8M0klwwsxNpLOHtjXSU4RvLfdgHnAtgZu+kEZBeinSUnbcRWNnMtvs14Bfu/u9h/bLjfsnO3WtmdhWwmUZmzZfcfZeZfQbY4u4bgf+XxnR8D42ZUU/nRjzxxngPbgEmAxua+Rz73H1ZxwYdgjHeh+PaGO/BZuD3zOwZoA5c5+4HOzfqiTfG+3ANcI+ZfZLGMtXHj7MPqpjZehpLsyc298r+DMgCuPv/oLF39kFgD1AE/iDU8Rxn91dERI5RSViyExGRY4ACkoiIxIICkoiIxIICkoiIxIICkoiIxIICkkiIzOz55lme4e//a9i/Q+RYo4AkEhIzS4/2PXf/9SjHInIsUEASacPM/quZrW5+/QUz+3bz63PN7D4zW2FmT5vZD83s5iF/74iZfcbMHgeWDnm/28y+aWZXDFzX/PO3zOwRM/uamf2bmf3DQKV5M/tg873vNXvS/GPz/Rlm9r+bfXq+yJB6Y2b2sJltbfYxWtV87w/N7AtDrrnCzG4L7+6JvDkKSCLtPQq8v/n1YmCymWWBs4EfAzcDvwMsAN5rZhc1r51Eo7fM+9z9e833JgP/C/iqu9/T5nctBK6m0XNnDvAbZtZFo5TTBe5+NjBzyPV/BnzP3RfSKO0ye8j3Lnf3Rc0xrzazGTRaKyxrjh8ap+3//pe+IyIhU0ASaW8rsMjMpgBl4DEaD/n3A68Cj7j7S812Jf9Ao9EZNErtPDjsZ30D+Ht3v3eU3/WEux9oVpHeAZwK/Edgb7O4KcD6IdefA9wH4O7/H/DKkO+tNrOnaNThOwWY6+59wLeBD5nZfwSy7v702G+FSDQUkETacPcq8DyN2cS/At+lUXD0V2kU3RxNyd3rw977PnDB6zR9HFpZvU6jxuQbNYgcUfPLzH4L+F1gqbufSaPra1fz239Ho62GZkcSWwpIIqN7FLi2+ed3gf9CYwbzA+A3zezEZuLCCuBfXufn/ClwEPjbX+J3/xswx8xObb7+yLBx/WcAM7sAOKH5/luAV9y92JwJ/drAX3D3x2nMmC6ldbYlEhsKSCKj+y7wNuAxd3+RRkvz7zbL798AfAd4Ctjm7t94g591NdBlZn89ll/s7v3AHwHfNLPvAS/S6GQM8N+Bc8xsG/B7HJ2xfRPImNlOGm3YfzDsxz4AfH+gNblI3Kjat0hMmdlkdz/SXOq7E/ixu3/hjf7e6/y8fwS+4O7/PGGDFJlAmiGJxNcVZrYD2EVjOe6Lb+aHmNk0M3sW6FcwkjjTDElERGJBMyQREYkFBSQREYkFBSQREYkFBSQREYkFBSQREYkFBSQREYmF/x9wrCuBiiFOZwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of only the highly correlated pairs\n",
    "for v,i,j in s_corr_list:\n",
    "    sns.pairplot(data, size=6, x_vars=cols[i],y_vars=cols[j] )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.4 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(731, 9)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 从原始数据中分离输入特征x和输出y\n",
    "y = data['cnt'].values\n",
    "X = data.drop(['cnt','instant','dteday','mnth','season','casual','registered'], axis = 1)\n",
    "#用于后续显示权重系数对应的特征\n",
    "columns = X.columns\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     yr  holiday  weekday  workingday  weathersit      temp     atemp  \\\n",
      "365   1        0        0           0           1  0.370000  0.375621   \n",
      "366   1        1        1           0           1  0.273043  0.252304   \n",
      "367   1        0        2           1           1  0.150000  0.126275   \n",
      "368   1        0        3           1           2  0.107500  0.119337   \n",
      "369   1        0        4           1           1  0.265833  0.278412   \n",
      "370   1        0        5           1           1  0.334167  0.340267   \n",
      "371   1        0        6           0           1  0.393333  0.390779   \n",
      "372   1        0        0           0           1  0.337500  0.340258   \n",
      "373   1        0        1           1           2  0.224167  0.247479   \n",
      "374   1        0        2           1           1  0.308696  0.318826   \n",
      "375   1        0        3           1           2  0.274167  0.282821   \n",
      "376   1        0        4           1           2  0.382500  0.381938   \n",
      "377   1        0        5           1           1  0.274167  0.249362   \n",
      "378   1        0        6           0           1  0.180000  0.183087   \n",
      "379   1        0        0           0           1  0.166667  0.161625   \n",
      "380   1        1        1           0           1  0.190000  0.190663   \n",
      "381   1        0        2           1           2  0.373043  0.364278   \n",
      "382   1        0        3           1           1  0.303333  0.275254   \n",
      "383   1        0        4           1           1  0.190000  0.190038   \n",
      "384   1        0        5           1           2  0.217500  0.220958   \n",
      "385   1        0        6           0           2  0.173333  0.174875   \n",
      "386   1        0        0           0           2  0.162500  0.162250   \n",
      "387   1        0        1           1           2  0.218333  0.243058   \n",
      "388   1        0        2           1           1  0.342500  0.349108   \n",
      "389   1        0        3           1           1  0.294167  0.294821   \n",
      "390   1        0        4           1           2  0.341667  0.356050   \n",
      "391   1        0        5           1           2  0.425000  0.415383   \n",
      "392   1        0        6           0           1  0.315833  0.326379   \n",
      "393   1        0        0           0           1  0.282500  0.272721   \n",
      "394   1        0        1           1           1  0.269167  0.262625   \n",
      "..   ..      ...      ...         ...         ...       ...       ...   \n",
      "701   1        0        0           0           2  0.347500  0.359208   \n",
      "702   1        0        1           1           1  0.452500  0.455796   \n",
      "703   1        0        2           1           1  0.475833  0.469054   \n",
      "704   1        0        3           1           1  0.438333  0.428012   \n",
      "705   1        0        4           1           1  0.255833  0.258204   \n",
      "706   1        0        5           1           2  0.320833  0.321958   \n",
      "707   1        0        6           0           2  0.381667  0.389508   \n",
      "708   1        0        0           0           2  0.384167  0.390146   \n",
      "709   1        0        1           1           2  0.435833  0.435575   \n",
      "710   1        0        2           1           2  0.353333  0.338363   \n",
      "711   1        0        3           1           2  0.297500  0.297338   \n",
      "712   1        0        4           1           1  0.295833  0.294188   \n",
      "713   1        0        5           1           1  0.281667  0.294192   \n",
      "714   1        0        6           0           1  0.324167  0.338383   \n",
      "715   1        0        0           0           2  0.362500  0.369938   \n",
      "716   1        0        1           1           2  0.393333  0.401500   \n",
      "717   1        0        2           1           1  0.410833  0.409708   \n",
      "718   1        0        3           1           1  0.332500  0.342162   \n",
      "719   1        0        4           1           2  0.330000  0.335217   \n",
      "720   1        0        5           1           2  0.326667  0.301767   \n",
      "721   1        0        6           0           1  0.265833  0.236113   \n",
      "722   1        0        0           0           1  0.245833  0.259471   \n",
      "723   1        0        1           1           2  0.231304  0.258900   \n",
      "724   1        1        2           0           2  0.291304  0.294465   \n",
      "725   1        0        3           1           3  0.243333  0.220333   \n",
      "726   1        0        4           1           2  0.254167  0.226642   \n",
      "727   1        0        5           1           2  0.253333  0.255046   \n",
      "728   1        0        6           0           2  0.253333  0.242400   \n",
      "729   1        0        0           0           1  0.255833  0.231700   \n",
      "730   1        0        1           1           2  0.215833  0.223487   \n",
      "\n",
      "          hum  windspeed  \n",
      "365  0.692500   0.192167  \n",
      "366  0.381304   0.329665  \n",
      "367  0.441250   0.365671  \n",
      "368  0.414583   0.184700  \n",
      "369  0.524167   0.129987  \n",
      "370  0.542083   0.167908  \n",
      "371  0.531667   0.174758  \n",
      "372  0.465000   0.191542  \n",
      "373  0.701667   0.098900  \n",
      "374  0.646522   0.187552  \n",
      "375  0.847500   0.131221  \n",
      "376  0.802917   0.180967  \n",
      "377  0.507500   0.378108  \n",
      "378  0.457500   0.187183  \n",
      "379  0.419167   0.251258  \n",
      "380  0.522500   0.231358  \n",
      "381  0.716087   0.349130  \n",
      "382  0.443333   0.415429  \n",
      "383  0.497500   0.220158  \n",
      "384  0.450000   0.202750  \n",
      "385  0.831250   0.222642  \n",
      "386  0.796250   0.199638  \n",
      "387  0.911250   0.110708  \n",
      "388  0.835833   0.123767  \n",
      "389  0.643750   0.161071  \n",
      "390  0.769583   0.073396  \n",
      "391  0.741250   0.342667  \n",
      "392  0.543333   0.210829  \n",
      "393  0.311250   0.240050  \n",
      "394  0.400833   0.215792  \n",
      "..        ...        ...  \n",
      "701  0.823333   0.124379  \n",
      "702  0.767500   0.082721  \n",
      "703  0.733750   0.174129  \n",
      "704  0.485000   0.324021  \n",
      "705  0.508750   0.174754  \n",
      "706  0.764167   0.130600  \n",
      "707  0.911250   0.101379  \n",
      "708  0.905417   0.157975  \n",
      "709  0.925000   0.190308  \n",
      "710  0.596667   0.296037  \n",
      "711  0.538333   0.162937  \n",
      "712  0.485833   0.174129  \n",
      "713  0.642917   0.131229  \n",
      "714  0.650417   0.106350  \n",
      "715  0.838750   0.100742  \n",
      "716  0.907083   0.098258  \n",
      "717  0.666250   0.221404  \n",
      "718  0.625417   0.184092  \n",
      "719  0.667917   0.132463  \n",
      "720  0.556667   0.374383  \n",
      "721  0.441250   0.407346  \n",
      "722  0.515417   0.133083  \n",
      "723  0.791304   0.077230  \n",
      "724  0.734783   0.168726  \n",
      "725  0.823333   0.316546  \n",
      "726  0.652917   0.350133  \n",
      "727  0.590000   0.155471  \n",
      "728  0.752917   0.124383  \n",
      "729  0.483333   0.350754  \n",
      "730  0.577500   0.154846  \n",
      "\n",
      "[366 rows x 9 columns]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(366, 9)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将数据分割训练数据与测试数据，训练集为2011年的数据，测试集为2012的数据\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 随机采样20%的数据构建测试样本，其余作为训练样本\n",
    "#X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0, test_size=366)\n",
    "X_train = X.loc[:364,:]\n",
    "X_test = X.loc[365:,:]\n",
    "y_train = y [:365]\n",
    "y_test = y[365:731]\n",
    "\n",
    "#print (X_train)\n",
    "print (X_test)\n",
    "X_test.shape\n",
    "#print (y_train)\n",
    "#print (y_test)\n",
    "#y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算2012年对2011年的增长率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = data.loc[:364,:]\n",
    "h = data.loc[365:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.0</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>183.000000</td>\n",
       "      <td>2.498630</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.526027</td>\n",
       "      <td>0.027397</td>\n",
       "      <td>3.008219</td>\n",
       "      <td>0.684932</td>\n",
       "      <td>1.421918</td>\n",
       "      <td>0.486665</td>\n",
       "      <td>0.466835</td>\n",
       "      <td>0.643665</td>\n",
       "      <td>0.191403</td>\n",
       "      <td>677.402740</td>\n",
       "      <td>2728.358904</td>\n",
       "      <td>3405.761644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>105.510663</td>\n",
       "      <td>1.110946</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.452584</td>\n",
       "      <td>0.163462</td>\n",
       "      <td>2.006155</td>\n",
       "      <td>0.465181</td>\n",
       "      <td>0.571831</td>\n",
       "      <td>0.189596</td>\n",
       "      <td>0.168836</td>\n",
       "      <td>0.148744</td>\n",
       "      <td>0.076890</td>\n",
       "      <td>556.269121</td>\n",
       "      <td>1060.110413</td>\n",
       "      <td>1378.753666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>431.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>92.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.325000</td>\n",
       "      <td>0.321954</td>\n",
       "      <td>0.538333</td>\n",
       "      <td>0.135583</td>\n",
       "      <td>222.000000</td>\n",
       "      <td>1730.000000</td>\n",
       "      <td>2132.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>183.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.479167</td>\n",
       "      <td>0.472846</td>\n",
       "      <td>0.647500</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>2915.000000</td>\n",
       "      <td>3740.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>274.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.656667</td>\n",
       "      <td>0.612379</td>\n",
       "      <td>0.742083</td>\n",
       "      <td>0.235075</td>\n",
       "      <td>871.000000</td>\n",
       "      <td>3632.000000</td>\n",
       "      <td>4586.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>365.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.849167</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3065.000000</td>\n",
       "      <td>4614.000000</td>\n",
       "      <td>6043.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season     yr        mnth     holiday     weekday  \\\n",
       "count  365.000000  365.000000  365.0  365.000000  365.000000  365.000000   \n",
       "mean   183.000000    2.498630    0.0    6.526027    0.027397    3.008219   \n",
       "std    105.510663    1.110946    0.0    3.452584    0.163462    2.006155   \n",
       "min      1.000000    1.000000    0.0    1.000000    0.000000    0.000000   \n",
       "25%     92.000000    2.000000    0.0    4.000000    0.000000    1.000000   \n",
       "50%    183.000000    3.000000    0.0    7.000000    0.000000    3.000000   \n",
       "75%    274.000000    3.000000    0.0   10.000000    0.000000    5.000000   \n",
       "max    365.000000    4.000000    0.0   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  365.000000  365.000000  365.000000  365.000000  365.000000  365.000000   \n",
       "mean     0.684932    1.421918    0.486665    0.466835    0.643665    0.191403   \n",
       "std      0.465181    0.571831    0.189596    0.168836    0.148744    0.076890   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.325000    0.321954    0.538333    0.135583   \n",
       "50%      1.000000    1.000000    0.479167    0.472846    0.647500    0.186900   \n",
       "75%      1.000000    2.000000    0.656667    0.612379    0.742083    0.235075   \n",
       "max      1.000000    3.000000    0.849167    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   365.000000   365.000000   365.000000  \n",
       "mean    677.402740  2728.358904  3405.761644  \n",
       "std     556.269121  1060.110413  1378.753666  \n",
       "min       9.000000   416.000000   431.000000  \n",
       "25%     222.000000  1730.000000  2132.000000  \n",
       "50%     614.000000  2915.000000  3740.000000  \n",
       "75%     871.000000  3632.000000  4586.000000  \n",
       "max    3065.000000  4614.000000  6043.000000  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.0</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "      <td>366.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>2.494536</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.513661</td>\n",
       "      <td>0.030055</td>\n",
       "      <td>2.986339</td>\n",
       "      <td>0.683060</td>\n",
       "      <td>1.368852</td>\n",
       "      <td>0.504081</td>\n",
       "      <td>0.481852</td>\n",
       "      <td>0.612166</td>\n",
       "      <td>0.189572</td>\n",
       "      <td>1018.483607</td>\n",
       "      <td>4581.450820</td>\n",
       "      <td>5599.934426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>105.799338</td>\n",
       "      <td>1.112185</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.455958</td>\n",
       "      <td>0.170971</td>\n",
       "      <td>2.006108</td>\n",
       "      <td>0.465921</td>\n",
       "      <td>0.516057</td>\n",
       "      <td>0.176112</td>\n",
       "      <td>0.156756</td>\n",
       "      <td>0.134206</td>\n",
       "      <td>0.078194</td>\n",
       "      <td>758.989897</td>\n",
       "      <td>1424.331846</td>\n",
       "      <td>1788.667868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.107500</td>\n",
       "      <td>0.101658</td>\n",
       "      <td>0.254167</td>\n",
       "      <td>0.046650</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>457.250000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.347708</td>\n",
       "      <td>0.350685</td>\n",
       "      <td>0.508125</td>\n",
       "      <td>0.133721</td>\n",
       "      <td>429.750000</td>\n",
       "      <td>3730.500000</td>\n",
       "      <td>4369.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.514167</td>\n",
       "      <td>0.497779</td>\n",
       "      <td>0.611875</td>\n",
       "      <td>0.174750</td>\n",
       "      <td>904.500000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5927.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>639.750000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.653958</td>\n",
       "      <td>0.607646</td>\n",
       "      <td>0.711146</td>\n",
       "      <td>0.231196</td>\n",
       "      <td>1262.000000</td>\n",
       "      <td>5663.000000</td>\n",
       "      <td>7011.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.804913</td>\n",
       "      <td>0.925000</td>\n",
       "      <td>0.441563</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season     yr        mnth     holiday     weekday  \\\n",
       "count  366.000000  366.000000  366.0  366.000000  366.000000  366.000000   \n",
       "mean   548.500000    2.494536    1.0    6.513661    0.030055    2.986339   \n",
       "std    105.799338    1.112185    0.0    3.455958    0.170971    2.006108   \n",
       "min    366.000000    1.000000    1.0    1.000000    0.000000    0.000000   \n",
       "25%    457.250000    2.000000    1.0    4.000000    0.000000    1.000000   \n",
       "50%    548.500000    2.500000    1.0    7.000000    0.000000    3.000000   \n",
       "75%    639.750000    3.000000    1.0    9.750000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.0   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  366.000000  366.000000  366.000000  366.000000  366.000000  366.000000   \n",
       "mean     0.683060    1.368852    0.504081    0.481852    0.612166    0.189572   \n",
       "std      0.465921    0.516057    0.176112    0.156756    0.134206    0.078194   \n",
       "min      0.000000    1.000000    0.107500    0.101658    0.254167    0.046650   \n",
       "25%      0.000000    1.000000    0.347708    0.350685    0.508125    0.133721   \n",
       "50%      1.000000    1.000000    0.514167    0.497779    0.611875    0.174750   \n",
       "75%      1.000000    2.000000    0.653958    0.607646    0.711146    0.231196   \n",
       "max      1.000000    3.000000    0.861667    0.804913    0.925000    0.441563   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   366.000000   366.000000   366.000000  \n",
       "mean   1018.483607  4581.450820  5599.934426  \n",
       "std     758.989897  1424.331846  1788.667868  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     429.750000  3730.500000  4369.000000  \n",
       "50%     904.500000  4776.500000  5927.000000  \n",
       "75%    1262.000000  5663.000000  7011.250000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.6442531836793448\n"
     ]
    }
   ],
   "source": [
    "increase = 5599.934426 / 3405.761644\n",
    "print (increase)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.5 数据预处理／特征工程\n",
    "\n",
    "特征工程是实际任务中特别重要的环节。\n",
    "\n",
    "scikit learn中提供的数据预处理功能：\n",
    "http://scikit-learn.org/stable/modules/preprocessing.html\n",
    "http://scikit-learn.org/stable/modules/classes.html#module- sklearn.feature_extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#发现各特征差异较大，需要进行数据标准化预处理\n",
    "#标准化的目的在于避免原始特征值差异过大，导致训练得到的参数权重不归一，无法比较各特征的重要性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n",
      "/home/chin/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n",
      "/home/chin/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    }
   ],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    " \n",
    "# 分别初始化对特征和目标值的标准化器\n",
    "ss_X = StandardScaler()\n",
    "ss_y = StandardScaler()\n",
    "\n",
    "# 分别对训练和测试数据的特征以及目标值进行标准化处理\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "X_test = ss_X.transform(X_test)\n",
    "\n",
    "#对y做标准化不是必须\n",
    "#对y标准化的好处是不同问题的w差异不太大，同时正则参数的范围也有限\n",
    "y_train = ss_y.fit_transform(y_train.reshape(-1, 1))\n",
    "y_test = ss_y.transform(y_test.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3、确定模型类型\n",
    "3.1 尝试缺省参数的线性回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>temp</td>\n",
       "      <td>[0.5044852023400006]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>atemp</td>\n",
       "      <td>[0.22950390476489457]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>weekday</td>\n",
       "      <td>[0.04347527600555068]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>workingday</td>\n",
       "      <td>[0.005284837121251426]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>yr</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>hum</td>\n",
       "      <td>[-0.008599751529943106]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>holiday</td>\n",
       "      <td>[-0.030404841405857974]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>[-0.16854087889402822]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>weathersit</td>\n",
       "      <td>[-0.22944163025828074]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      columns                     coef\n",
       "5        temp     [0.5044852023400006]\n",
       "6       atemp    [0.22950390476489457]\n",
       "2     weekday    [0.04347527600555068]\n",
       "3  workingday   [0.005284837121251426]\n",
       "0          yr                    [0.0]\n",
       "7         hum  [-0.008599751529943106]\n",
       "1     holiday  [-0.030404841405857974]\n",
       "8   windspeed   [-0.16854087889402822]\n",
       "4  weathersit   [-0.22944163025828074]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 线性回归\n",
    "#class sklearn.linear_model.LinearRegression(fit_intercept=True, normalize=False, copy_X=True, n_jobs=1)\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "# 使用默认配置初始化\n",
    "lr = LinearRegression()\n",
    "\n",
    "# 训练模型参数\n",
    "lr.fit(X_train, y_train)\n",
    "\n",
    "# 预测\n",
    "y_test_pred_lr = lr.predict(X_test)\n",
    "y_train_pred_lr = lr.predict(X_train)\n",
    "\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef\":list((lr.coef_.T))})\n",
    "fs.sort_values(by=['coef'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.1.1 模型评价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LinearRegression on test is 0.8861698724935942\n",
      "The r2 score of LinearRegression on train is 0.6882763062934556\n"
     ]
    }
   ],
   "source": [
    "# 使用r2_score评价模型在测试集和训练集上的性能，并输出评估结果\n",
    "#测试集\n",
    "print ('The r2 score of LinearRegression on test is', r2_score(y_test, y_test_pred_lr)+ increase)\n",
    "#训练集\n",
    "print ('The r2 score of LinearRegression on train is', r2_score(y_train, y_train_pred_lr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#在训练集上观察预测残差的分布，看是否符合模型假设：噪声为0均值的高斯噪声\n",
    "f, ax = plt.subplots(figsize=(7, 5)) \n",
    "f.tight_layout() \n",
    "ax.hist(y_train - y_train_pred_lr,bins=40, label='Residuals Linear', color='b', alpha=.5); \n",
    "ax.set_title(\"Histogram of Residuals\") \n",
    "ax.legend(loc='best');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#还可以观察预测值与真值的散点图\n",
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_train, y_train_pred_lr)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('True')\n",
    "plt.ylabel('Predict')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py:578: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.        , -0.03016469,  0.04334755,  0.00530836, -0.2281139 ,\n",
       "        0.43069059,  0.30352189, -0.00893215, -0.16741825])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 线性模型，随机梯度下降优化模型参数\n",
    "# 随机梯度下降一般在大数据集上应用，其实本项目不适合用\n",
    "from sklearn.linear_model import SGDRegressor\n",
    "\n",
    "# 使用默认配置初始化线\n",
    "sgdr = SGDRegressor(max_iter=1000)\n",
    "\n",
    "# 训练：参数估计\n",
    "sgdr.fit(X_train, y_train)\n",
    "\n",
    "# 预测\n",
    "#sgdr_y_predict = sgdr.predict(X_test)\n",
    "\n",
    "sgdr.coef_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.2 正则化的线性回归（L2正则 --> 岭回归）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of RidgeCV on test is 0.8816435764965296\n",
      "The r2 score of RidgeCV on train is 0.688038438852326\n"
     ]
    }
   ],
   "source": [
    "#岭回归／L2正则\n",
    "#class sklearn.linear_model.RidgeCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, \n",
    "#                                  normalize=False, scoring=None, cv=None, gcv_mode=None, \n",
    "#                                  store_cv_values=False)\n",
    "from sklearn.linear_model import  RidgeCV\n",
    "\n",
    "#设置超参数（正则参数）范围\n",
    "alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "#n_alphas = 20\n",
    "#alphas = np.logspace(-5,2,n_alphas)\n",
    "\n",
    "#生成一个RidgeCV实例\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "\n",
    "#模型训练\n",
    "ridge.fit(X_train, y_train)    \n",
    "\n",
    "#预测\n",
    "y_test_pred_ridge = ridge.predict(X_test)\n",
    "y_train_pred_ridge = ridge.predict(X_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print ('The r2 score of RidgeCV on test is', r2_score(y_test, y_test_pred_ridge) + increase )\n",
    "print ('The r2 score of RidgeCV on train is', r2_score(y_train, y_train_pred_ridge))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 10.0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>temp</td>\n",
       "      <td>[0.5044852023400006]</td>\n",
       "      <td>[0.37563613912823896]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>atemp</td>\n",
       "      <td>[0.22950390476489457]</td>\n",
       "      <td>[0.3501047658116536]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>weekday</td>\n",
       "      <td>[0.04347527600555068]</td>\n",
       "      <td>[0.04169153408979076]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>workingday</td>\n",
       "      <td>[0.005284837121251426]</td>\n",
       "      <td>[0.005212798607842073]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>yr</td>\n",
       "      <td>[0.0]</td>\n",
       "      <td>[0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>hum</td>\n",
       "      <td>[-0.008599751529943106]</td>\n",
       "      <td>[-0.011555220776019781]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>holiday</td>\n",
       "      <td>[-0.030404841405857974]</td>\n",
       "      <td>[-0.029102475345045065]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>[-0.16854087889402822]</td>\n",
       "      <td>[-0.16363163238528858]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>weathersit</td>\n",
       "      <td>[-0.22944163025828074]</td>\n",
       "      <td>[-0.22213558925283966]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      columns                  coef_lr               coef_ridge\n",
       "5        temp     [0.5044852023400006]    [0.37563613912823896]\n",
       "6       atemp    [0.22950390476489457]     [0.3501047658116536]\n",
       "2     weekday    [0.04347527600555068]    [0.04169153408979076]\n",
       "3  workingday   [0.005284837121251426]   [0.005212798607842073]\n",
       "0          yr                    [0.0]                    [0.0]\n",
       "7         hum  [-0.008599751529943106]  [-0.011555220776019781]\n",
       "1     holiday  [-0.030404841405857974]  [-0.029102475345045065]\n",
       "8   windspeed   [-0.16854087889402822]   [-0.16363163238528858]\n",
       "4  weathersit   [-0.22944163025828074]   [-0.22213558925283966]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "#这是为了标出最佳参数的位置，不是必须\n",
    "#plt.plot(np.log10(ridge.alpha_)*np.ones(3), [0.28, 0.29, 0.30])\n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "print ('alpha is:', ridge.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.3 正则化的线性回归（L1正则 --> Lasso）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LassoCV on test is 0.8462542623947256\n",
      "The r2 score of LassoCV on train is 0.6823218301028284\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chin/anaconda3/lib/python3.6/site-packages/sklearn/linear_model/coordinate_descent.py:1094: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    }
   ],
   "source": [
    "#### Lasso／L1正则\n",
    "# class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, \n",
    "#                                    normalize=False, precompute=’auto’, max_iter=1000, \n",
    "#                                    tol=0.0001, copy_X=True, cv=None, verbose=False, n_jobs=1,\n",
    "#                                    positive=False, random_state=None, selection=’cyclic’)\n",
    "from sklearn.linear_model import LassoCV\n",
    "\n",
    "#设置超参数搜索范围\n",
    "#alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "\n",
    "#生成一个LassoCV实例\n",
    "#lasso = LassoCV(alphas=alphas)  \n",
    "lasso = LassoCV()  \n",
    "\n",
    "#训练（内含CV）\n",
    "lasso.fit(X_train, y_train)  \n",
    "\n",
    "#测试\n",
    "y_test_pred_lasso = lasso.predict(X_test)\n",
    "y_train_pred_lasso = lasso.predict(X_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print ('The r2 score of LassoCV on test is', r2_score(y_test, y_test_pred_lasso) + increase)\n",
    "print ('The r2 score of LassoCV on train is', r2_score(y_train, y_train_pred_lasso))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.03598594627336977\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>columns</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "      <th>coef_lasso</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>temp</td>\n",
       "      <td>[0.5044852023400006]</td>\n",
       "      <td>[0.37563613912823896]</td>\n",
       "      <td>0.358046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>atemp</td>\n",
       "      <td>[0.22950390476489457]</td>\n",
       "      <td>[0.3501047658116536]</td>\n",
       "      <td>0.345155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>weekday</td>\n",
       "      <td>[0.04347527600555068]</td>\n",
       "      <td>[0.04169153408979076]</td>\n",
       "      <td>0.006149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>workingday</td>\n",
       "      <td>[0.005284837121251426]</td>\n",
       "      <td>[0.005212798607842073]</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>yr</td>\n",
       "      <td>[0.0]</td>\n",
       "      <td>[0.0]</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>hum</td>\n",
       "      <td>[-0.008599751529943106]</td>\n",
       "      <td>[-0.011555220776019781]</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>holiday</td>\n",
       "      <td>[-0.030404841405857974]</td>\n",
       "      <td>[-0.029102475345045065]</td>\n",
       "      <td>-0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>windspeed</td>\n",
       "      <td>[-0.16854087889402822]</td>\n",
       "      <td>[-0.16363163238528858]</td>\n",
       "      <td>-0.132291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>weathersit</td>\n",
       "      <td>[-0.22944163025828074]</td>\n",
       "      <td>[-0.22213558925283966]</td>\n",
       "      <td>-0.202030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      columns                  coef_lr               coef_ridge  coef_lasso\n",
       "5        temp     [0.5044852023400006]    [0.37563613912823896]    0.358046\n",
       "6       atemp    [0.22950390476489457]     [0.3501047658116536]    0.345155\n",
       "2     weekday    [0.04347527600555068]    [0.04169153408979076]    0.006149\n",
       "3  workingday   [0.005284837121251426]   [0.005212798607842073]    0.000000\n",
       "0          yr                    [0.0]                    [0.0]    0.000000\n",
       "7         hum  [-0.008599751529943106]  [-0.011555220776019781]   -0.000000\n",
       "1     holiday  [-0.030404841405857974]  [-0.029102475345045065]   -0.000000\n",
       "8   windspeed   [-0.16854087889402822]   [-0.16363163238528858]   -0.132291\n",
       "4  weathersit   [-0.22944163025828074]   [-0.22213558925283966]   -0.202030"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "fs = pd.DataFrame({\"columns\":list(columns), \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T)), \"coef_lasso\":list((lasso.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha is: 0.03598594627336977\n"
     ]
    }
   ],
   "source": [
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
